Abstract

We present an approach for reconstructing land surface temperature (LST) time series over mountainous areas based on Regression Kriging (RK) technique and a data processing scheme for filtering out LST noise and artifacts. A total of 1462 eight-day composite Moderate Resolution Imaging Spectroradiometer LST images over central Qinghai-Tibet Plateau over 2003-2010 are reconstructed. The regression model includes four auxiliary predictors-latitude, longitude, elevation, and NDVI-which are proven to be a good estimator for the 8-day LST. Comparison of ground surface temperature (GST) measurements at eight meteorological stations with the raw and reconstructed LST series shows that the reconstruction strategy can effectively recover complete high-quality over-land LST maps and significantly improve the consistency between LST and GST.

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